Federated learning for intrusion detection in IoT environments: a privacy-preserving strategy

Federated learning for intrusion detection in IoT environments: a privacy-preserving strategy

Abstract The rapid expansion of IoT devices has introduced significant cybersecurity risks, as attackers increasingly exploit these networks’ vulnerabilities. To counter this threat, this paper presents the Privacy-Enhanced IoT Defence System (PEIoT-DS), a novel solution that emphasises data privacy...

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Bibliographic Details
Main Authors: Ansam Khraisat, Ammar Alazab, Moutaz Alazab, Areej Obeidat, Sarabjot Singh, Tony Jan
Format: Article
Language:English
Published: Springer 2025-06-01
Series:Discover Internet of Things
Subjects:
Federated learning
Data privacy
Communication network security
Anomaly detection
Intrusion detection system
Online Access:https://doi.org/10.1007/s43926-025-00169-7
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